Adaptive rate and reach optimization for wireless access networks

ABSTRACT

A method controls a wireless network, which includes a controller and a plurality of network elements. The method includes determining interference in the wireless network using radio-link measurements, generating an interference matrix identifying the interference in the wireless network, and generating an adjacency matrix based on the interference matrix identifying locations having unacceptable levels of interference in the wireless network. The method also includes allocating channels and corresponding transmission powers in the wireless network to reduce the unacceptable levels of interference. The method is performed at predetermined fixed time intervals and when a new network element is added to the wireless network.

This application is a continuation of pending U.S. patent applicationSer. No. 13/270,542, filed on Oct. 11, 2011, which is a continuation ofU.S. patent application Ser. No. 11/432,490, filed on May 12, 2006, nowU.S. Pat. No. 8,064,413, issued on Nov. 22, 2011, the disclosures ofwhich are expressly incorporated herein by reference in theirentireties.

BACKGROUND

1. Field of the Disclosure

The present disclosure relates to wireless communications. Moreparticularly, the present disclosure relates to controlling wirelesslocal area networks (WLANs).

2. Background Information

Over the past several years, computer networks have become increasinglymobile. One wireless local area networking (WLAN) technology is WiFi,i.e., 802.11. WiFi is a member of the IEEE 802 family, which is a seriesof specifications for local area network (LAN) technologies. In thisfamily, there are other well-known specifications such as 802.3, i.e.,Ethernet. Another WLAN technology is WiMax defined by the IEEE 802.16standard.

WLANs complement existing fixed networks by providing mobility to users,just as mobile telephones complement fixed wireline telephony. Theadvantage of mobility is gained by employing a much more open networkmedium: free space. However, as free space lacks a physical boundary,signals can be sent or received by any device complying with the WLANstandard and therefore different WLANs in a geographical region mayinterfere with each other. Wireless users in a home WiFi network oftenobserve the presence of several WiFi LANs in their neighborhood. Someeven detect that the signal of a neighbor's wireless router is muchstronger than their own. When WLANs interfere with each other,connection speed in each LAN is adversely impacted and the aggregatethroughput of the WLANs (consisting of all WLANs in one geographicalarea) is reduced.

Currently, there exist simple methods to reduce the interference betweenWLANs. Individual WiFi Access Points (AP) or WiFi routers may implementTransmit Power Control (TPC) and Dynamic Frequency Selection (DFS)services specified in the 802.11x standard. However, TPC and DFS do notaim at global optimization because they are independently and optionallyimplemented by individual WiFi LANs.

Without a central capacity and performance management system, it isunlikely for WLANs to coordinate with each other and to achieve overallmaximum capacity. With WLANs becoming more and more popular and theinterference between WLANs occurring more often, the lack of centralcapacity and performance management is severely degrading theperformance of WLANs by reducing the connection speed of individuallinks and the aggregate throughput of the whole network.

There is a need for addressing the issues identified above.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an exemplary general computer system that can operatewithin the WLAN system;

FIG. 2 shows an exemplary WLAN system including a dynamic performancemanagement system, according to an aspect of the present invention;

FIG. 3 shows an exemplary interference matrix, according to an aspect ofthe present invention;

FIG. 4 shows an exemplary adjacency matrix, according to an aspect ofthe present invention;

FIG. 5 shows an exemplary graph corresponding to the adjacency matrix ofFIG. 4, according to an aspect of the present invention; and

FIG. 6 shows an exemplary colored graph, according to an aspect of thepresent invention.

DETAILED DESCRIPTION

In view of the foregoing, the present disclosure, through one or more ofits various aspects, embodiments and/or specific features orsub-components, is thus intended to bring out one or more of theadvantages as specifically noted below.

The present disclosure pertains to a centralized dynamic performancemanagement (DPM) system for wireless networks consisting of independentwireless LANs, such as WiFi LANs and WiMax networks. The dynamicperformance management system can coordinate the operation ofindependent WLANs and improve aggregate WLAN throughput.

In one aspect of the present invention, a computer readable mediumstores a program for controlling network elements of wireless local areanetworks (WLANs). The program includes a WLAN network element pollingcode segment that receives interference data from the WLAN networkelements, the interference data indicating network elements thatinterfere with the WLAN network elements. The program has afrequency/power determination code segment that determines a frequencyand/or transmission power level for each WLAN network element to reduceinterference with the interfering network elements. The program also hasa transmitting code segment that transmits instructions to each WLANnetwork element to control the frequency and/or transmission power levelof the WLAN network elements.

The WLANs can be 802.11 networks and/or 802.16 networks. In oneembodiment, the instructions are a dynamic frequency selection (DFS)instruction and/or a transmit power control (TPC) instruction.

The frequency/power determination code segment can determine that thepower level should be an increased power level when a signal attenuationvalue between an access point and a client is above a threshold value.

The frequency/power determination code segment can determine thefrequency and/or the transmission power level by generating an adjacencymatrix based upon the received interference data. The frequency and/orthe transmission power level can be determined by graph coloring basedupon the generated adjacency matrix. The graph coloring can include anumber of colors that is equal to a number of channels available in theWLANs. The transmission power level can be a reduced power level for atleast one of the WLAN network elements when the graph coloring requiresmore than the number of colors in order to reduce interference.

In another aspect, a dynamic performance management system controlswireless networks. The system includes a receiver that receivesinterference data from WLAN network elements, the interference dataindicating network elements that interfere with the WLAN networkelements. The system also includes a frequency/power determinationsystem that determines a frequency and/or transmission power level foreach WLAN network element to reduce interference with the interferingnetwork elements. The system also has a transmitter that transmitsinstructions to each WLAN network element to control the frequencyand/or transmission power level of the WLAN network elements.

In still another aspect, a wireless local area network (WLAN) controlsystem includes access points that measure signal attenuation incommunications with other WLAN network elements. The system also has adynamic performance management system that receives signal attenuationdata from the access points, determines a frequency and/or transmissionpower level for each of the access points to reduce interference withthe other WLAN network elements, and transmits instructions to eachaccess point to control the frequency and/or transmission power level ofthe access points.

In yet another aspect, a method for controlling network elements ofwireless local area networks (WLANs) includes receiving interferencedata from the WLAN network elements, the interference data indicatingnetwork elements that interfere with the WLAN network elements. Themethod also includes determining a frequency and/or transmission powerlevel for each WLAN network element to reduce interference with theinterfering network elements. The method further includes transmittinginstructions to each WLAN network element to control the frequencyand/or transmission power level of the WLAN network elements.

According to an aspect of the disclosure, the aggregate throughput andreach of a wireless access networks, such as a WiFi or WiMax network, isimproved through a dynamic performance management (DPM) system. Thedynamic performance management system collects performance data frommultiple devices and adaptively improves the rate and reach usingadaptive and self learning controls, such as Transmit Power Control(TPC) and Dynamic Frequency Selection (DFS). Although the followingdescription primarily refers to WiFi networks, the present inventioncontemplates alternative WLANs, such as WiMax networks.

FIG. 2 shows representative WiFis network with a centralized dynamicperformance management (DPM) system 40. In FIG. 2, three access points(AP) 10, 20, 30 each have a corresponding coverage area 12, 22, 32. AWiFi client 14, 24, 34 is located in each coverage area 12, 22, 32 toenable communications with the corresponding access point 10, 20, 30. Inthis description, it is assumed that each access point only serves asingle client for the sake of simplicity. Of course multiple clients canbe served by an access point and more than three access points could beprovided. The dynamic performance management system 40 connects to eachaccess point 10, 20, 30 via a network 50, such as the Internet.

Each access point 10, 20, 30 may be connected to a distribution systemsuch as a wired Ethernet (not shown), or they can lie in independentWiFi LANs with no direct connection between each other. The latter caseis representative of a residential WiFi network, where each premise hasan independent wireless LAN which connects to the Internet through, forexample, DSL, cable or fiber. These wireless LANs do not communicatewith each other.

During the network initiation phase, the dynamic performance managementsystem 40 coordinates all access points 10, 20, 30 and clients 14, 24,34 to conduct a medium characterization so as to obtain performancedata, e.g., the signal attenuation, between any two WiFi devices (AP orclient). Although signal attenuation is discussed, alternativeinterference measurements could be substituted, such as signal to noiseratio. Moreover, interference with outside sources, such as RADAR couldbe detected.

In an embodiment, interference is measured by a radio link measurement.For example, access point 10 sends a beacon to access point 20 with afixed signal strength, such as 0 dBm. If access point 20 receives thesignal and the power is −10 dBm, then the attenuation is determined tobe 10 dB. Each network element attempts to communicate with each othernetwork element in this manner to obtain a complete picture of networkinterference.

At the end of characterization, the dynamic performance managementsystem 40 populates an interference matrix. FIG. 3 shows an exemplarypopulated interference matrix. In FIG. 3, the value of a cell specifiesthe signal attenuation from the row WiFi device to the column WiFidevice. For example, access point 10 has a 30 dB signal attenuation withrespect to access point 20.

Based upon the interference matrix, an adjacency matrix can begenerated. FIG. 4 shows a simplified adjacency matrix based upon theinterference matrix of FIG. 3. The adjacency matrix is simplified inthat it only show access points 10, 20, 30, and not clients 14, 24, 34.However, the concept equally applies to clients as well as access pointsand any other network elements. In FIG. 4, an “x” in a cell indicatesthat the row WiFi device has an unacceptable level of interference withthe column WiFi device. For example, FIG. 4 indicates that access point10 has an unacceptable level of interference with access point 20, andalso that access point 20 has an unacceptable level of interference withaccess point 30. Acceptable attenuation values are well known, and themeasured values are compared with the acceptable values to determinewhether unacceptable interference exists.

The connection speed between each access point/client pair, and hencethe aggregate WiFi throughput, depends on the channel frequencyallocation and the interference matrix of FIG. 3. As this dependencyusually can be expressed analytically or numerically, the dynamicperformance management system 40 will be able to improve (or possiblymaximize) the overall WiFi throughput by optimizing the channelfrequency allocation and transmit power for each access point/clientpair. Under the control of the dynamic performance management system 40,some access point/client pairs may have to reduce transmit power if theyare interfering severely with other access point/client pairs. On thecontrary, some access point/client pairs may be able to use higher powerthan that specified by TPC service when the pair is far away from otheraccess point/client pairs and therefore unlikely to impact them. Forexample, if the signal attenuation between an access point and itsassociated client is high, it is known that more power is needed. Theconverse can also be true, which could reduce interference with otheraccess points and clients.

An adjacency matrix for different networks can be generated based on theinterference matrix and the known acceptable levels of interference.Based upon the adjacency matrix, the dynamic performance managementsystem 40 can then optimally allocate appropriate channels for eachnetwork so that the interference is reduced (e.g., minimized). In oneembodiment, the technique employed is called “graph coloring.”

The adjacency matrix (e.g., as shown in FIG. 4) can be modeled as agraph by creating a vertex for each network element. An edge existsbetween two vertices A and B if there is an “x” marked at both cell(A:B) and cell (B:A). For example, the cell corresponding to accesspoint 10 and access point 20, as well as the cell corresponding toaccess point 20 and access point 10 both contain an “x.” Thus, an edgeexists between access point 10 and access point 20, as shown in FIG. 5.Similarly, the cell corresponding to access point 20 and access point30, as well as the cell corresponding to access point 30 and accesspoint 20 both contain an “x.” Thus, an edge exists between access point20 and access point 30, as also shown in FIG. 5.

The vertices of the graph can then be colored in a way such that noadjacent vertices have the same color, or in other words, no interferingnetworks are assigned the same channel. When two interfering networksare assigned different channels, or frequencies, the interferencebetween these two networks is significantly reduced. As a result, thechannel assignment problem for wireless access networks to reduceinterference can be equated to coloring the corresponding graph so thatadjacent vertices have different colors.

FIG. 6 shows the coloring results of the graph of FIG. 5. In FIG. 6, itcan be seen that access point 20 is a different “color” than accesspoint 10 and access point 30. That is, the shaded representation ofaccess point 20 is different from the non-shaded representation ofaccess points 10 and 30. Of course, in a color drawing, colors would beused instead of dotted and solid lines.

WiFi networks typically have 14 different channels (or 12 in somecountries). Consequently, the dynamic performance management system 40colors the corresponding graph with a maximum of 14 (or 12) colors. Asthe size of a WiFi network grows, it may become impossible to color theWiFi network with only 14 colors. In that case, the dynamic performancemanagement system 40 can prune the number of edges in the correspondinggraph so that 14 colors (or 12 colors) are enough. In other words, somevertices will have their power reduced (e.g., in an ad hoc manner) sothat a smaller graph results from the interference analysis. In oneembodiment, newly added nodes will have their power adjusted first.

Both access point and client may be mobile, implying the channelattenuation between them may vary frequently. Even when access point andclient are fixed, the channel attenuation can still vary due to thetemporal change of the wireless medium. In one embodiment, theabove-described analysis is repeated every two weeks to compensate forthe dynamic nature of the attenuation. In addition, a new access pointor client may join in the WiFi network. When a new network element joinsthe WLAN, the interference matrix also needs to be dynamically changed.Whenever the channel attenuation matrix is updated, the dynamicperformance management system 40 should decide if the allocation ofchannel frequency and transmit power for each access point/client pairshould change in order to improve the aggregate WiFi throughput.Therefore, the dynamic performance management system 40 and themechanism to improve aggregate WiFi throughput are both adaptive.

In summary, the dynamic performance management system architectureincludes an adaptive data collection and monitoring centralized system;a dynamic and self learning performance control and provisioning system;and a reporting subsystem and network management console.

Referring to FIG. 1, a description is now provided of an illustrativeembodiment of a general computer system 100, on which the centralizedWLAN control functionality can be implemented. The computer system 100can include a set of instructions that can be executed to cause thecomputer system 100 to perform any one or more of the methods orcomputer based functions disclosed herein. The computer system 100 mayoperate as a standalone device or may be connected, e.g., using anetwork 101, to other computer systems or peripheral devices.

In a networked deployment, the computer system may operate in thecapacity of a server or as a client user computer in a server-clientuser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 100 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a land-line telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In a particularembodiment, the computer system 100 can be implemented using electronicdevices that provide voice, video or data communication. Further, whilea single computer system 100 is illustrated, the term “system” shallalso be taken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As illustrated in FIG. 1, the computer system 100 may include aprocessor 110, e.g., a central processing unit (CPU), a graphicsprocessing unit (GPU), or both. Moreover, the computer system 100 caninclude a main memory 120 and a static memory 130 that can communicatewith each other via a bus 108. As shown, the computer system 100 mayfurther include a video display unit 150, such as a liquid crystaldisplay (LCD), an organic light emitting diode (OLED), a flat paneldisplay, a solid state display, or a cathode ray tube (CRT).Additionally, the computer system 100 may include an input device 160,such as a keyboard, and a cursor control device 170, such as a mouse.The computer system 100 can also include a disk drive unit 180, a signalgeneration device 190, such as a speaker or remote control, and anetwork interface device 140.

In a particular embodiment, as depicted in FIG. 1, the disk drive unit180 may include a computer-readable medium 182 in which one or more setsof instructions 184, e.g. software, can be embedded. Further, theinstructions 184 may embody one or more of the methods or logic asdescribed herein. In a particular embodiment, the instructions 184 mayreside completely, or at least partially, within the main memory 120,the static memory 130, and/or within the processor 110 during executionby the computer system 100. The main memory 120 and the processor 110also may include computer-readable media.

In an alternative embodiment, dedicated hardware implementations, suchas application specific integrated circuits, programmable logic arraysand other hardware devices, can be constructed to implement one or moreof the methods described herein. Applications that may include theapparatus and systems of various embodiments can broadly include avariety of electronic and computer systems. One or more embodimentsdescribed herein may implement functions using two or more specificinterconnected hardware modules or devices with related control and datasignals that can be communicated between and through the modules, or asportions of an application-specific integrated circuit. Accordingly, thepresent system encompasses software, firmware, and hardwareimplementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

The present disclosure contemplates a computer-readable medium 182 thatincludes instructions 184 or receives and executes instructions 184responsive to a propagated signal so that a device connected to anetwork 101 can communicate voice, video or data over the network 101.Further, the instructions 184 may be transmitted or received over thenetwork 101 via the network interface device 140.

While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. A digital file attachment to an e-mail or other self-containedinformation archive or set of archives may be considered a distributionmedium that is equivalent to a tangible storage medium. Accordingly, thedisclosure is considered to include any one or more of acomputer-readable medium or a distribution medium and other equivalentsand successor media, in which data or instructions may be stored.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the invention is not limited to suchstandards and protocols. Each of the standards, protocols and languagesrepresent examples of the state of the art. Such standards areperiodically superseded by faster or more efficient equivalents havingessentially the same functions. Accordingly, replacement standards andprotocols having the same or similar functions are consideredequivalents thereof.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R.§1.72(b) and is submitted with the understanding that it will not beused to interpret or limit the scope or meaning of the claims. Inaddition, in the foregoing Detailed Description, various features may begrouped together or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

The above disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover all suchmodifications, enhancements, and other embodiments which fall within thetrue spirit and scope of the present invention. Thus, to the maximumextent allowed by law, the scope of the present invention is to bedetermined by the broadest permissible interpretation of the followingclaims and their equivalents, and shall not be restricted or limited bythe foregoing detailed description.

Although the invention has been described with reference to severalexemplary embodiments, it is understood that the words that have beenused are words of description and illustration, rather than words oflimitation. Changes may be made within the purview of the appendedclaims, as presently stated and as amended, without departing from thescope and spirit of the invention in its aspects. Although the inventionhas been described with reference to particular means, materials andembodiments, the invention is not intended to be limited to theparticulars disclosed; rather, the invention extends to all functionallyequivalent structures, methods, and uses such as are within the scope ofthe appended claims.

What is claimed is:
 1. A method for controlling a wireless network,which includes a controller and a plurality of network elements, themethod comprising: determining interference in the wireless networkusing radio-link measurements; generating an interference matrixidentifying the interference in the wireless network; generating anadjacency matrix based on the interference matrix identifying locationshaving unacceptable levels of interference in the wireless network; andallocating channels and corresponding transmission powers in thewireless network to reduce the unacceptable levels of interference;wherein the method is performed at predetermined fixed time intervalsand when a new network element is added to the wireless network.
 2. Themethod according to claim 1, wherein a network element of the pluralityof network elements is a mobile device.
 3. The method according to claim1, wherein the predetermined fixed time intervals are a predeterminednumber of hours.
 4. The method according to claim 1, wherein thepredetermined fixed time intervals are a predetermined number of days.5. The method according to claim 1, wherein the predetermined fixed timeintervals are restarted after the method is performed due to a newnetwork element being added to the wireless network.
 6. The methodaccording to claim 1, wherein the plurality of network elements includea plurality of access points and a plurality of clients, with eachaccess point serving at least one client.
 7. The method according toclaim 6, wherein the plurality of access points includes an access pointthat has an independent wireless local area network that is connected tothe Internet.
 8. The method according to claim 7, wherein theindependent wireless local area network is connected to the Internetthrough a coaxial cable.
 9. The method according to claim 7, wherein theindependent wireless local area network is connected to the Internetthrough a fiber-optic transmission system.
 10. The method according toclaim 1, wherein the determining interference in the wireless network isperformed by polling the plurality of network elements.
 11. The methodaccording to claim 1, wherein the unacceptable levels of interferenceare reduced dynamically by adaptive self-learning controls.
 12. Themethod according to claim 11, wherein the adaptive self-learningcontrols include dynamic frequency selection.
 13. The method accordingto claim 1, further comprising: modeling the adjacency matrix as a graphby creating a vertex for each network element, wherein the graph iscolored such that no adjacent vertices have the same color, each colorrepresenting a communication channel.
 14. The method according to claim13, wherein each color represents one communication channel of apredetermined number of available communication channels.
 15. The methodaccording to claim 13, further comprising: pruning at least one edge ofthe graph of the adjacency matrix so that the graph does not exceed thepredetermined number of available communication channels when at leastone additional network element is added to the local area network. 16.The method according to claim 15, wherein the pruning includes reducingpower to at least one vertex.
 17. The method according to claim 13,wherein the graph is colored using a maximum of 14 colors.
 18. Themethod according to claim 15, wherein a most recently added networkelement has power reduced by the pruning.
 19. A tangible storage mediumencoded with an executable computer program for controlling a wirelessnetwork that, when executed by a processor, causes the processor toperform operations comprising: determining interference in the wirelessnetwork using radio-link measurements; generating an interference matrixidentifying the interference in the wireless network; generating anadjacency matrix based on the interference matrix identifying locationshaving unacceptable levels of interference in the wireless network; andallocating channels and corresponding transmission powers in thewireless network to reduce the unacceptable levels of interference;wherein the method is performed at predetermined fixed time intervalsand when a new network element is added to the wireless network.
 20. Aserver for controlling a wireless network, which includes a plurality ofnetwork elements, the server comprising: a processor for determininginterference in the wireless network, wherein the processor generates aninterference matrix identifying the interference in the wirelessnetwork, wherein the processor generates an adjacency matrix based onthe interference matrix identifying locations having unacceptable levelsof interference, and allocating channels and corresponding transmissionpowers in the wireless network to reduce the unacceptable levels ofinterference; a storage for storing the interference matrix and theadjacency matrix; wherein the processor generates the interferencematrix, generates the adjacency matrix, and allocates the channels andthe corresponding transmission powers at predetermined fixed timeintervals and when a new network element is added to the wirelessnetwork.